832 resultados para Multi-particle systems


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Peer-reviewed

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The model of Questions Answering (Q&A) for eLearning is based on collaborative learning through questions that are posed by students and their answers to that questions which are given by peers, in contrast with the classical model in which students ask questions to the teacher only. In this proposal we extend the Q&A model including the social presence concept and a quantitative measure of it is proposed; besides it is considered the evolution of the resulting Q&A social network after the inclusion of the social presence and taking into account the feedback on questions posed by students and answered by peers. The social network behaviorwas simulated using a Multi-Agent System to compare the proposed social presence model with the classical and the Q&A models

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Dirt counting and dirt particle characterisation of pulp samples is an important part of quality control in pulp and paper production. The need for an automatic image analysis system to consider dirt particle characterisation in various pulp samples is also very critical. However, existent image analysis systems utilise a single threshold to segment the dirt particles in different pulp samples. This limits their precision. Based on evidence, designing an automatic image analysis system that could overcome this deficiency is very useful. In this study, the developed Niblack thresholding method is proposed. The method defines the threshold based on the number of segmented particles. In addition, the Kittler thresholding is utilised. Both of these thresholding methods can determine the dirt count of the different pulp samples accurately as compared to visual inspection and the Digital Optical Measuring and Analysis System (DOMAS). In addition, the minimum resolution needed for acquiring a scanner image is defined. By considering the variation in dirt particle features, the curl shows acceptable difference to discriminate the bark and the fibre bundles in different pulp samples. Three classifiers, called k-Nearest Neighbour, Linear Discriminant Analysis and Multi-layer Perceptron are utilised to categorize the dirt particles. Linear Discriminant Analysis and Multi-layer Perceptron are the most accurate in classifying the segmented dirt particles by the Kittler thresholding with morphological processing. The result shows that the dirt particles are successfully categorized for bark and for fibre bundles.

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This work reports on the investigation of nanosized CeO2-ZnO systems prepared by Pechini's method. The structural and morphological characterization of CeO2-ZnO systems as well as the characterization of CeO2 and ZnO separately, showed that the employed method result in powders with spheroidal particles whose size are in the range 30 - 200 nm, which is appropriate to provide homogeneous suspensions. The ZnO present in the prepared mixed oxides seems to increase particle size distribution and to influence the arrangement of the particles after powder dispersion.

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The use of fertilizers and solid amendments in agriculture generates special interest for their effect on crop productivity, as well as for their environmental impact. The efficient use of these products demands knowing their physical and mechanical properties, the storing conditions effect and the operational characteristics of the metering systems used in the fertilizing equipment. In this context, the present study was developed with the purpose of evaluating the operational characteristics of different fertilizing metering systems and to determine the adequate metering system-product operational parameters, using powder lime, powder gypsum, granular 10-30-10 (N-P-K), and granular urea. Operational differences were established among four types of commercial fertilizer metering systems, including wire auger, star-shaped feed wheel, feed screw and ridged traction wheel. The study found that the unloading rate depends directly on the fertilizer metering system's rotating speed and is affected by particle size, repose angle, bulk density and moisture content of the applied product. The wire auger and star-shaped feed wheel metering systems were adequate for the distribution of powder products and the feed screw for granulated fertilizers. Furthermore, theoretical and experimental characteristic equations were established, defining curves for calibration and handling of the products plus the rotating speed range in which a better distributing behavior was achieved.

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ABSTRACT Tractor traveling speed can influence the quality of spraying depending on the application technology used. This study aimed to evaluate the droplet spectrum, the deposition and uniformity of spray distribution with different spraying systems and traveling speeds of a self-propelled sprayer in two phenological stages of the cotton plant (B9 and F13). The experimental design was randomized blocks and treatments were three spraying techniques: common flat spray tips; tilted flat jet with air induction, at 120 L ha-1; and rotary atomizer disk, 20 L ha-1, combined with four traveling speeds: 12, 15, 18 and 25 km h-1, with four replications. Spraying deposition was evaluated for both leaf surfaces from the cotton plant apex and base (stage B9) and middle part of the plant (stage F13) with a cupric marker. A laser particle analyzer also assessed the droplet spectrum. The centrifugal power spray system produces more homogeneous droplet spectrum and increased penetration of droplets into the canopy in both phenological stages. Variation on the operating conditions necessary for increased traveling speed negatively influences the pattern of spraying deposits.

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More than ever, education organisations are experiencing the need to develop new services and processes to satisfy expanding and changing customer needs and to adapt to the environmental changes and continually tightening economic situation. Innovation has been found in many studies to have a crucial role in the success of an organisation, both in the private and public sectors, in formal education and in manufacturing and services alike. However, studies concerning innovation in non-formal adult education organisations, such as adult education centres (AECs) in Finland, are still lacking. This study investigates innovation in the non-formal adult education organisation context from the perspective of organisational culture types and social networks. The objective is to determine the significant characteristics of an innovative non-formal adult education organisation. The analysis is based on data from interviews with the principals and fulltime staff of four case AECs. Before the case study, a pre-study phase is accomplished in order to obtain a preliminary understanding of innovation at AECs. The research found strong support for the need of innovation in AECs. Innovation is basically needed to accomplish the AEC system’s primary mission mentioned in the ACT on Liberal Adult Education. In addition, innovation is regarded vital to institutes and may prevent their decline. It helps the institutes to be more attractive, to enter new market, to increase customer satisfaction and to be on the cutting edge. Innovation is also seen as a solution to the shortage of resources. Innovative AECs search actively for additional resources for development work through project funding and subsidies, cooperation networks and creating a conversational and joyful atmosphere in the institute. The findings also suggest that the culture type that supports innovation at AECs is multidimensional, with an emphasis on the clan and adhocratic culture types and such values as: dynamism, future orientation, acquiring new resources, mistake tolerance, openness, flexibility, customer orientation, a risk-taking attitude, and community spirit. Active and creative internal and external cooperation also promote innovation at AECs. This study also suggests that the behaviour of a principal is crucial. The way he or she shows appreciation the staff, encouragement and support to the staff and his or her approachability and concrete participation in innovation activities have a strong effect on innovation attitudes and activities in AECs.

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Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.

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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Personalized nanomedicine has been shown to provide advantages over traditional clinical imaging, diagnosis, and conventional medical treatment. Using nanoparticles can enhance and clarify the clinical targeting and imaging, and lead them exactly to the place in the body that is the goal of treatment. At the same time, one can reduce the side effects that usually occur in the parts of the body that are not targets for treatment. Nanoparticles are of a size that can penetrate into cells. Their surface functionalization offers a way to increase their sensitivity when detecting target molecules. In addition, it increases the potential for flexibility in particle design, their therapeutic function, and variation possibilities in diagnostics. Mesoporous nanoparticles of amorphous silica have attractive physical and chemical characteristics such as particle morphology, controllable pore size, and high surface area and pore volume. Additionally, the surface functionalization of silica nanoparticles is relatively straightforward, which enables optimization of the interaction between the particles and the biological system. The main goal of this study was to prepare traceable and targetable silica nanoparticles for medical applications with a special focus on particle dispersion stability, biocompatibility, and targeting capabilities. Nanoparticle properties are highly particle-size dependent and a good dispersion stability is a prerequisite for active therapeutic and diagnostic agents. In the study it was shown that traceable streptavidin-conjugated silica nanoparticles which exhibit a good dispersibility could be obtained by the suitable choice of a proper surface functionalization route. Theranostic nanoparticles should exhibit sufficient hydrolytic stability to effectively carry the medicine to the target cells after which they should disintegrate and dissolve. Furthermore, the surface groups should stay at the particle surface until the particle has been internalized by the cell in order to optimize cell specificity. Model particles with fluorescently-labeled regions were tested in vitro using light microscopy and image processing technology, which allowed a detailed study of the disintegration and dissolution process. The study showed that nanoparticles degrade more slowly outside, as compared to inside the cell. The main advantage of theranostic agents is their successful targeting in vitro and in vivo. Non-porous nanoparticles using monoclonal antibodies as guiding ligands were tested in vitro in order to follow their targeting ability and internalization. In addition to the targeting that was found successful, a specific internalization route for the particles could be detected. In the last part of the study, the objective was to clarify the feasibility of traceable mesoporous silica nanoparticles, loaded with a hydrophobic cancer drug, being applied for targeted drug delivery in vitro and in vivo. Particles were provided with a small molecular targeting ligand. In the study a significantly higher therapeutic effect could be achieved with nanoparticles compared to free drug. The nanoparticles were biocompatible and stayed in the tumor for a longer time than a free medicine did, before being eliminated by renal excretion. Overall, the results showed that mesoporous silica nanoparticles are biocompatible, biodegradable drug carriers and that cell specificity can be achieved both in vitro and in vivo.

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In recent years, technological advancements in microelectronics and sensor technologies have revolutionized the field of electrical engineering. New manufacturing techniques have enabled a higher level of integration that has combined sensors and electronics into compact and inexpensive systems. Previously, the challenge in measurements was to understand the operation of the electronics and sensors, but this has now changed. Nowadays, the challenge in measurement instrumentation lies in mastering the whole system, not just the electronics. To address this issue, this doctoral dissertation studies whether it would be beneficial to consider a measurement system as a whole from the physical phenomena to the digital recording device, where each piece of the measurement system affects the system performance, rather than as a system consisting of small independent parts such as a sensor or an amplifier that could be designed separately. The objective of this doctoral dissertation is to describe in depth the development of the measurement system taking into account the challenges caused by the electrical and mechanical requirements and the measurement environment. The work is done as an empirical case study in two example applications that are both intended for scientific studies. The cases are a light sensitive biological sensor used in imaging and a gas electron multiplier detector for particle physics. The study showed that in these two cases there were a number of different parts of the measurement system that interacted with each other. Without considering these interactions, the reliability of the measurement may be compromised, which may lead to wrong conclusions about the measurement. For this reason it is beneficial to conceptualize the measurement system as a whole from the physical phenomena to the digital recording device where each piece of the measurement system affects the system performance. The results work as examples of how a measurement system can be successfully constructed to support a study of sensors and electronics.

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This thesis addresses the coolability of porous debris beds in the context of severe accident management of nuclear power reactors. In a hypothetical severe accident at a Nordic-type boiling water reactor, the lower drywell of the containment is flooded, for the purpose of cooling the core melt discharged from the reactor pressure vessel in a water pool. The melt is fragmented and solidified in the pool, ultimately forming a porous debris bed that generates decay heat. The properties of the bed determine the limiting value for the heat flux that can be removed from the debris to the surrounding water without the risk of re-melting. The coolability of porous debris beds has been investigated experimentally by measuring the dryout power in electrically heated test beds that have different geometries. The geometries represent the debris bed shapes that may form in an accident scenario. The focus is especially on heap-like, realistic geometries which facilitate the multi-dimensional infiltration (flooding) of coolant into the bed. Spherical and irregular particles have been used to simulate the debris. The experiments have been modeled using 2D and 3D simulation codes applicable to fluid flow and heat transfer in porous media. Based on the experimental and simulation results, an interpretation of the dryout behavior in complex debris bed geometries is presented, and the validity of the codes and models for dryout predictions is evaluated. According to the experimental and simulation results, the coolability of the debris bed depends on both the flooding mode and the height of the bed. In the experiments, it was found that multi-dimensional flooding increases the dryout heat flux and coolability in a heap-shaped debris bed by 47–58% compared to the dryout heat flux of a classical, top-flooded bed of the same height. However, heap-like beds are higher than flat, top-flooded beds, which results in the formation of larger steam flux at the top of the bed. This counteracts the effect of the multi-dimensional flooding. Based on the measured dryout heat fluxes, the maximum height of a heap-like bed can only be about 1.5 times the height of a top-flooded, cylindrical bed in order to preserve the direct benefit from the multi-dimensional flooding. In addition, studies were conducted to evaluate the hydrodynamically representative effective particle diameter, which is applied in simulation models to describe debris beds that consist of irregular particles with considerable size variation. The results suggest that the effective diameter is small, closest to the mean diameter based on the number or length of particles.

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This research focuses on generating aesthetically pleasing images in virtual environments using the particle swarm optimization (PSO) algorithm. The PSO is a stochastic population based search algorithm that is inspired by the flocking behavior of birds. In this research, we implement swarms of cameras flying through a virtual world in search of an image that is aesthetically pleasing. Virtual world exploration using particle swarm optimization is considered to be a new research area and is of interest to both the scientific and artistic communities. Aesthetic rules such as rule of thirds, subject matter, colour similarity and horizon line are all analyzed together as a multi-objective problem to analyze and solve with rendered images. A new multi-objective PSO algorithm, the sum of ranks PSO, is introduced. It is empirically compared to other single-objective and multi-objective swarm algorithms. An advantage of the sum of ranks PSO is that it is useful for solving high-dimensional problems within the context of this research. Throughout many experiments, we show that our approach is capable of automatically producing images satisfying a variety of supplied aesthetic criteria.

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Population-based metaheuristics, such as particle swarm optimization (PSO), have been employed to solve many real-world optimization problems. Although it is of- ten sufficient to find a single solution to these problems, there does exist those cases where identifying multiple, diverse solutions can be beneficial or even required. Some of these problems are further complicated by a change in their objective function over time. This type of optimization is referred to as dynamic, multi-modal optimization. Algorithms which exploit multiple optima in a search space are identified as niching algorithms. Although numerous dynamic, niching algorithms have been developed, their performance is often measured solely on their ability to find a single, global optimum. Furthermore, the comparisons often use synthetic benchmarks whose landscape characteristics are generally limited and unknown. This thesis provides a landscape analysis of the dynamic benchmark functions commonly developed for multi-modal optimization. The benchmark analysis results reveal that the mechanisms responsible for dynamism in the current dynamic bench- marks do not significantly affect landscape features, thus suggesting a lack of representation for problems whose landscape features vary over time. This analysis is used in a comparison of current niching algorithms to identify the effects that specific landscape features have on niching performance. Two performance metrics are proposed to measure both the scalability and accuracy of the niching algorithms. The algorithm comparison results demonstrate the algorithms best suited for a variety of dynamic environments. This comparison also examines each of the algorithms in terms of their niching behaviours and analyzing the range and trade-off between scalability and accuracy when tuning the algorithms respective parameters. These results contribute to the understanding of current niching techniques as well as the problem features that ultimately dictate their success.